Secondary structure defining database and methods for determining identity and geographic origin of an unknown bioagent for environmental testing thereby

ABSTRACT

The present invention relates generally to the field of investigational bioinformatics and more particularly to secondary structure defining databases. The present invention further relates to methods for interrogating a database as a source of molecular masses of known bioagents for comparing against the molecular mass of an unknown or selected bioagent to determine either the identity of the selected bioagent, and/or to determine the origin of the selected bioagent. The identification of the bioagent is important for determining a proper course of treatment and/or irradication of the bioagent in such cases as biological warfare. Furthermore, the determination of the geographic origin of a selected bioagent will facilitate the identification of potential criminal identity.

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is a continuation-in-part of U.S. Ser. No.09/891,793 filed Jun. 26, 2001, which is incorporated herein byreference in its entirety.

STATEMENT OF GOVERNMENT SUPPORT

[0002] This invention was made with United States Government supportunder DARPA/SPO contract BAA00-09. The United States Government may havecertain rights in the invention.

FIELD OF THE INVENTION

[0003] The present invention relates generally to the field ofinvestigational bioinformatics and more particularly to secondarystructure defining databases. The present invention further relates tomethods for interrogating a database as a source of molecular masses ofknown bioagents for comparing against the molecular mass of an unknownor selected bioagent to determine either the identity of the selectedbioagent, and/or to determine the origin of the selected bioagent. Theidentification of the bioagent is important for determining a propercourse of treatment and/or irradication of the bioagent in such cases asbiological warfare. Furthermore, the determination of the geographicorigin of a selected bioagent will facilitate the identification ofpotential criminal identity. The present invention also relates tomethods for rapid detection and identification of bioagents fromenvironmental, clinical or other samples. The methods provide fordetection and characterization of a unique base composition signature(BCS) from any bioagent, including bacteria and viruses. The unique BCSis used to rapidly identify the bioagent.

BACKGROUND OF THE INVENTION

[0004] In the United States, hospitals report well over 5 million casesof recognized infectious disease-related illnesses annually.Significantly greater numbers remain undetected, both in the inpatientand community setting, resulting in substantial morbidity and mortality.Critical intervention for infectious disease relies on rapid, sensitiveand specific detection of the offending pathogen, and is central to themission of microbiology laboratories at medical centers. Unfortunately,despite the recognition that outcomes from infectious illnesses aredirectly associated with time to pathogen recognition, as well asaccurate identification of the class and species of microbe, and abilityto identify the presence of drug resistance isolates, conventionalhospital laboratories often remain encumbered by traditional slowmulti-step culture based assays. Other limitations of the conventionallaboratory which have become increasingly apparent include: extremelyprolonged wait-times for pathogens with long generation time (up toseveral weeks); requirements for additional testing and wait times forspeciation and identification of antimicrobial resistance; diminishedtest sensitivity for patients who have received antibiotics; andabsolute inability to culture certain pathogens in disease statesassociated with microbial infection.

[0005] For more than a decade, molecular testing has been heralded asthe diagnostic tool for the new millennium, whose ultimate potentialcould include forced obsolescence of traditional hospital laboratories.However, despite the fact that significant advances in clinicalapplication of PCR techniques have occurred, the practicing physicianstill relies principally on standard techniques. A brief discussion ofseveral existing applications of PCR in the hospital-based settingfollows.

[0006] Generally speaking molecular diagnostics have been championed foridentifying organisms that cannot be grown in vitro, or in instanceswhere existing culture techniques are insensitive and/or requireprolonged incubation times. PCR-based diagnostics have been successfullydeveloped for a wide variety of microbes. Application to the clinicalarena has met with variable success, with only a few assays achievingacceptance and utility.

[0007] One of the earliest, and perhaps most widely recognizedapplications of PCR for clinical practice is in detection ofMycobacterium tuberculosis. Clinical characteristics favoringdevelopment of a nonculture-based test for tuberculosis include week tomonth long delays associated with standard testing, occurrence ofdrug-resistant isolates and public health imperatives associated withrecognition, isolation and treatment. Although frequently used as adiagnostic adjunctive, practical and routine clinical application of PCRremains problematic due to significant inter-laboratory variation insensitivity, and inadequate specificity for use in low prevalencepopulations, requiring further development at the technical level.Recent advances in the laboratory suggest that identification of drugresistant isolates by amplification of mutations associated withspecific antibiotic resistance (e.g., rpoB gene in rifampin resistantstrains) may be forthcoming for clinical use, although widespreadapplication will require extensive clinical validation.

[0008] One diagnostic assay, which has gained widespread acceptance, isfor C. trachomatis. Conventional detection systems are limiting due toinadequate sensitivity and specificity (direct immunofluoresence orenzyme immunoassay) or the requirement for specialized culturefacilities, due to the fastidious characteristics of this microbe.Laboratory development, followed by widespread clinical validationtesting in a variety of acute and nonacute care settings havedemonstrated excellent sensitivity (90-100%) and specificity (97%) ofthe PCR assay leading to its commercial development. Proven efficacy ofthe PCR assay from both genital and urine sampling, have resulted in itsapplication to a variety of clinical setting, most recently includingroutine screening of patients considered at risk. While the fullpotential for PCR diagnostics to provide rapid and critical informationto physicians faced with difficult clinical-decisions has yet to berealized, one recently developed assay provides an example of thepromise of this evolving technology. Distinguishing life-threateningcauses of fever from more benign causes in children is a fundamentalclinical dilemma faced by clinicians, particularly when infections ofthe central nervous system are being considered. Bacterial causes ofmeningitis can be highly aggressive, but generally cannot bedifferentiated on a clinical basis from aseptic meningitis, which is arelatively benign condition that can be managed on an outpatient basis.Existing blood culture methods often take several days to turn positive,and are often confounded by poor sensitivity or false-negative findingsin patients receiving empiric antimicrobials. Testing and application ofa PCR assay for enteroviral meningitis has been found to be highlysensitive. With reporting of results within 1 day, preliminary clinicaltrials have shown significant reductions in hospital costs, due todecreased duration of hospital stays and reduction in antibiotictherapy. Other viral PCR assays, now routinely available include thosefor herpes simplex virus, cytomegalovirus, hepatitis and HIV. Each has ademonstrated cost savings role in clinical practice, including detectionof otherwise difficult to diagnose infections and newly realizedcapacity to monitor progression of disease and response to therapy,vital in the management of chronic infectious diseases.

[0009] The concept of a universal detection system has been forwardedfor identification of bacterial pathogens, and speaks most directly tothe possible clinical implications of a broad-based screening tool forclinical use. Exploiting the existence of highly conserved regions ofDNA common to all bacterial species in a PCR assay would empowerphysicians to rapidly identify the presence of bacteremia, which wouldprofoundly impact patient care. Previous empiric decision making couldbe abandoned in favor of educated practice, allowing appropriate andexpeditious decision-making regarding need for antibiotic therapy andhospitalization.

[0010] Experimental work using the conserved features of the 16S rRNAcommon to almost all bacterial species, is an area of activeinvestigation. Hospital test sites have focused on “high yield” clinicalsettings where expeditious identification of the presence of systemicbacterial infection has immediate high morbidity and mortalityconsequences. Notable clinical infections have included evaluation offebrile infants at risk for sepsis, detection of bacteremia in febrileneutropenic cancer patients, and examination of critically ill patientsin the intensive care unit. While several of these studies have reportedpromising results (with sensitivity and specificity well over 90%),significant technical difficulties (described below) remain, and haveprevented general acceptance of this assay in clinics and hospitals(which remain dependent on standard blood culture methodologies). Eventhe revolutionary advances of real-time PCR technique, which offers aquantitative more reproducible and technically simpler system, remainsencumbered by inherent technical limitations of the PCR assay.

[0011] The principle shortcomings of applying PCR assays to the clinicalsetting include: inability to eliminate background DNA contamination;interference with the PCR amplification by substrates present in thereaction; and limited capacity to provide rapid reliable speciation,antibiotic resistance and subtype identification. Some laboratories haverecently made progress in identifying and removing inhibitors; howeverbackground contamination remains problematic, and methods directedtowards eliminating exogenous sources of DNA report significantdiminution in assay sensitivity. Finally, while product identificationand detailed characterization has been achieved using sequencingtechniques, these approaches are laborious and time-intensive thusdetracting from its clinical applicability.

[0012] Rapid and definitive microbial identification is desirable for avariety of industrial, medical, environmental, quality, and researchreasons. Traditionally, the microbiology laboratory has functioned toidentify the etiologic agents of infectious diseases through directexamination and culture of specimens. Since the mid-1980s, researchershave repeatedly demonstrated the practical utility of molecular biologytechniques, many of which form the basis of clinical diagnostic assays.Some of these techniques include nucleic acid hybridization analysis,restriction enzyme analysis, genetic sequence analysis, and separationand purification of nucleic acids (See, e.g., J. Sambrook, E. F.Fritsch, and T. Maniatis, Molecular Cloning: A Laboratory Manual, 2ndEd., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.,1989). These procedures, in general, are time-consuming and tedious.Another option is the polymerase chain reaction (PCR) or otheramplification procedure that amplifies a specific target DNA sequencebased on the flanking primers used. Finally, detection and data analysisconvert the hybridization event into an analytical result.

[0013] Other not yet fully realized applications of PCR for clinicalmedicine is the identification of infectious causes of diseasepreviously described as idiopathic (e.g. Bartonella henselae inbacillary angiomatosis, and Tropheryma whippellii as the unculturedbacillus associated with Whipple's disease). Further, recentepidemiological studies which suggest a strong association betweenChlamydia pneumonia and coronary artery disease, serve as example of thepossible widespread, yet undiscovered links between pathogen and hostwhich may ultimately allow for new insights into pathogenesis and novellife sustaining or saving therapeutics.

[0014] For the practicing clinician, PCR technology offers a yetunrealized potential for diagnostic omnipotence in the arena ofinfectious disease. A universal reliable infectious disease detectionsystem would certainly become a fundamental tool in the evolvingdiagnostic armamentarium of the 21^(st) century clinician. For frontline emergency physicians, or physicians working in disaster settings, aquick universal detection system, would allow for molecular triage andearly aggressive targeted therapy. Preliminary clinical studies usingspecies specific probes suggest that implementing rapid testing in acutecare setting is feasible. Resources could thus be appropriately applied,and patients with suspected infections could rapidly be risk stratifiedto the different treatment settings, depending on the pathogen andvirulence. Furthermore, links with data management systems, locallyregionally and nationally, would allow for effective epidemiologicalsurveillance, with obvious benefits for antibiotic selection and controlof disease outbreaks.

[0015] For the hospitalists, the ability to speciate and subtype wouldallow for more precise decision-making regarding antimicrobial agents.Patients who are colonized with highly contagious pathogens could beappropriately isolated on entry into the medical setting without delay.Targeted therapy will diminish development of antibiotic resistance.Furthermore, identification of the genetic basis of antibiotic resistantstrains would permit precise pharmacologic intervention. Both physicianand patient would benefit with less need for repetitive testing andelimination of wait times for test results.

[0016] It is certain that the individual patient will benefit directlyfrom this approach. Patients with unrecognized or difficult to diagnoseinfections would be identified and treated promptly. There will bereduced need for prolonged inpatient stays, with resultant decreases inlatrogenic events.

[0017] Mass spectrometry provides detailed information about themolecules being analyzed, including high mass accuracy. It is also aprocess that can be easily automated. Low-resolution MS may beunreliable when used to detect some known agents, if their spectrallines are sufficiently weak or sufficiently close to those from otherliving organisms in the sample. DNA chips with specific probes can onlydetermine the presence or absence of specifically anticipated organisms.Because there are hundreds of thousands of species of benign bacteria,some very similar in sequence to threat organisms, even arrays with10,000 probes lack the breadth needed to detect a particular organism.

[0018] Antibodies face more severe diversity limitations than arrays. Ifantibodies are designed against highly conserved targets to increasediversity, the false alarm problem will dominate, again because threatorganisms are very similar to benign ones. Antibodies are only capableof detecting known agents in relatively uncluttered environments.

[0019] Several groups have described detection of PCR products usinghigh resolution electrospray ionization-Fourier transform-ion cyclotronresonance mass spectrometry (ESI-FT-ICR MS). Accurate measurement ofexact mass combined with knowledge of the number of at least onenucleotide allowed calculation of the total base composition for PCRduplex products of approximately 100 base pairs. (Aaserud et al., J. Am.Soc. Mass Spec., 1996, 7, 1266-1269; Muddiman et al., Anal. Chem., 1997,69, 1543-1549; Wunschel et al., Anal. Chem., 1998, 70, 1203-1207;Muddiman et al, Rev. Anal. Chem., 1998, 17, 1-68). Electrosprayionization-Fourier transform-ion cyclotron resistance (ESI-FT-ICR) MSmay be used to determine the mass of double-stranded, 500 base-pair PCRproducts via the average molecular mass (Hurst et al., Rapid Commun.Mass Spec. 1996, 10, 377-382). The use of matrix-assisted laserdesorption ionization-time of flight (MALDI-TOF) mass spectrometry forcharacterization of PCR products has been described. (Muddiman et al.,Rapid Commun. Mass Spec., 1999, 13, 1201-1204). However, the degradationof DNAs over about 75 nucleotides observed with MALDI limited theutility of this method.

[0020] U.S. Pat. No. 5,849,492 describes a method for retrieval ofphylogenetically informative DNA sequences which comprise searching fora highly divergent segment of genomic DNA surrounded by two highlyconserved segments, designing the universal primers for PCRamplification of the highly divergent region, amplifying the genomic DNAby PCR technique using universal primers, and then sequencing the geneto determine the identity of the organism.

[0021] U.S. Pat. No. 5,965,363 discloses methods for screening nucleicacids for polymorphisms by analyzing amplified target nucleic acidsusing mass spectrometric techniques and to procedures for improving massresolution and mass accuracy of these methods.

[0022] WO 99/14375 describes methods, PCR primers and kits for use inanalyzing preselected DNA tandem nucleotide repeat alleles by massspectrometry.

[0023] WO 98/12355 discloses methods of determining the mass of a targetnucleic acid by mass spectrometric analysis, by cleaving the targetnucleic acid to reduce its length, making the target single-stranded andusing MS to determine the mass of the single-stranded shortened target.Also disclosed are methods of preparing a double-stranded target nucleicacid for MS analysis comprising amplification of the target nucleicacid, binding one of the strands to a solid support, releasing thesecond strand and then releasing the first strand which is then analyzedby MS. Kits for target nucleic acid preparation are also provided.

[0024] PCT WO97/33000 discloses methods for detecting mutations in atarget nucleic acid by nonrandomly fragmenting the target into a set ofsingle-stranded nonrandom length fragments and determining their massesby MS.

[0025] U.S. Pat. No. 5,605,798 describes a fast and highly accurate massspectrometer-based process for detecting the presence of a particularnucleic acid in a biological sample for diagnostic purposes.

[0026] WO 98/21066 describes processes for determining the sequence of aparticular target nucleic acid by mass spectrometry. Processes fordetecting a target nucleic acid present in a biological sample by PCRamplification and mass spectrometry detection are disclosed, as aremethods for detecting a target nucleic acid in a sample by amplifyingthe target with primers that contain restriction sites and tags,extending and cleaving the amplified nucleic acid, and detecting thepresence of extended product, wherein the presence of a DNA fragment ofa mass different from wild-type is indicative of a mutation. Methods ofsequencing a nucleic acid via mass spectrometry methods are alsodescribed.

[0027] WO 97/37041, WO 99/31278 and U.S. Pat. No. 5,547,835 describemethods of sequencing nucleic acids using mass spectrometry. U.S. Pat.Nos. 5,622,824, 5,872,003 and 5,691,141 describe methods, systems andkits for exonuclease-mediated mass spectrometric sequencing.

[0028] Thus, there is a need for a method for bioagent detection andidentification which is both specific and rapid, and in which no nucleicacid sequencing is required. The present invention addresses this need.

SUMMARY OF THE INVENTION

[0029] The present invention is directed to methods of identifying anunknown bioagent in an environmental sample using a database, such as adatabase stored on, for example, a local computer or perhaps a databaseaccessible over a network or on the internet. This database of molecularmasses of known bioagents provides a standard of comparison fordetermining both identity and geographic origin of the unknown bioagentin the environmental sample. The nucleic acid from the bioagent is firstcontacted with at least one pair of oligonucleotide primers whichhybridize to sequences of said nucleic acid that flank a variablenucleic acid sequence of the bioagent. Using PCR technology anamplification product of this variable nucleic acid sequence is made.After standard isolation, the molecular mass of this amplificationproduct is determined using known mass-spec techniques. This molecularmass is compared to the molecular mass of known bioagents within thedatabase, for identifying the unknown bioagent in the environmentalsample. In other aspects of the invention, environmental samplesinclude, but are not limited to, water, land, air, and the like. Watersamples can be obtained from, for example, lakes, rivers, oceans,streams, water treatment systems, rainwater, groundwater, water table,reservoirs, wells, bottled water, and the like. Air samples can beobtained from ventilation systems, airplane cabins, schools, hospitals,mass transit locations such as subways, train stations, airports, andthe like. Conditions such as sick building syndrome can be detected.Land samples can be obtained from any location.

[0030] This invention is also directed to databases having cell-datapositional significance comprising at least a first table that includesa plurality of data-containing cells. The table is organized into atleast a first row and a second row, each row having columns which arealigned relative to each other so that inter-row conserved regions arealigned. This alignment facilitates the analysis of regions, which arehighly conserved between species. This alignment further providesinsight into secondary polymer structure by this alignment. Althoughthis invention is directed to a database where each row describes anypolymer in an environmental sample, in a preferred embodiment, thepolymer is an RNA. Other alignments that operate in the same manner arealso contemplated.

[0031] Another embodiment is directed to determining the geographicorigin of a bioagent in an environmental sample using a database ofmolecular masses of known bioagents comprising contacting a nucleic acidfrom the selected bioagent in the environmental sample with at least onepair of oligonucleotide primers which hybridize to sequences of thenucleic acid, where the sequences flank a variable nucleic acid sequenceof the bioagent. This hybridized region is isolated and amplifiedthrough standard PCR techniques known in the art. The molecular mass isdetermined of this amplified product through any technique known in theart such as, Mass-spectrometry for example. This molecular mass iscompared to the molecular masses stored in the database of knownbioagents thereby determining a group of probabilistically reasonablegeographic origins for the selected bioagent.

BRIEF DESCRIPTION OF THE DRAWINGS

[0032] FIGS. 1A-1H and FIG. 2 are consensus diagrams that show examplesof conserved regions from 16S rRNA (FIGS. 1A, 1A-2, 1A-3, 1A-4, 1B,1B-1, and 1B-2), 23S rRNA (3′-half, FIGS. 1C-1, 1C-2, and ID; 5′-half,FIGS. 1E-F), 23S rRNA Domain I (FIG. 1G), 23S rRNA Domain IV (FIG. 1H)and 16S rRNA Domain III (FIG. 2) which are suitable for use in thepresent invention. Where there is overlap or redundancy between thefigures, the overlap is simply provided as an orientation aid and noadditional members of the sequence are implied thereby. Lines witharrows are examples of regions to which intelligent primer pairs for PCRare designed. The label for each primer pair represents the starting andending base number of the amplified region on the consensus diagram.Bases in capital letters are greater than 95% conserved; bases in lowercase letters are 90-95% conserved, filled circles are 80-90% conserved;and open circles are less than 80% conserved. The label for each primerpair represents the starting and ending base number of the amplifiedregion on the consensus diagram. The nucleotide sequence of the 16S rRNAconsensus sequence is SEQ ID NO:3 and the nucleotide sequence of the 23SrRNA consensus sequence is SEQ ID NO:4.

[0033]FIG. 2 shows a typical primer amplified region from the 16S rRNADomain III shown in FIG. 1C.

[0034]FIG. 3 is a schematic diagram showing conserved regions in RNaseP. Bases in capital letters are greater than 90% conserved; bases inlower case letters are 80-90% conserved; filled circles designate baseswhich are 70-80% conserved; and open circles designate bases that areless than 70% conserved.

[0035]FIG. 4 is a schematic diagram of base composition signaturedetermination using nucleotide analog “tags” to determine basecomposition signatures.

[0036]FIG. 5 shows the deconvoluted mass spectra of a Bacillus anthracisregion with and without the mass tag phosphorothioate A (A*). The twospectra differ in that the measured molecular weight of the masstag-containing sequence is greater than the unmodified sequence.

[0037]FIG. 6 shows base composition signature (BCS) spectra from PCRproducts from Staphylococcus aureus (S. aureus 16S_(—)1337F) andBacillus anthracus (B. anthr. 16S_(—)1337F), amplified using the sameprimers. The two strands differ by only two (AT—>CG) substitutions andare clearly distinguished on the basis of their BCS.

[0038]FIG. 7 shows that a single difference between two sequences (A14in B. anthracis vs. A15 in B. cereus) can be easily detected usingESI-TOF mass spectrometry.

[0039]FIG. 8 is an ESI-TOF of Bacillus anthracis spore coat protein sspE56mer plus calibrant. The signals unambiguously identify B. anthracisversus other Bacillus species.

[0040]FIG. 9 is an ESI-TOF of a B. anthracis synthetic 16S_(—)1228duplex (reverse and forward strands). The technique easily distinguishesbetween the forward and reverse strands.

[0041]FIG. 10 is an ESI-FTICR-MS of a synthetic B. anthracis 16S_(—)133746 base pair duplex.

[0042]FIG. 11 is an ESI-TOF-MS of a 56mer oligonucleotide (3 scans) fromthe B. anthracis saspB gene with an internal mass standard. The internalmass standards are designated by asterisks.

[0043]FIG. 12 is an ESI-TOF-MS of an internal standard with 5 mM TBA-TFAbuffer showing that charge stripping with tributylammoniumtrifluoroacetate reduces the most abundant charge state from [M-8H+]8-to [M-3H+]3-.

[0044]FIG. 13 is a portion of a secondary structure defining databaseaccording to one embodiment of the present invention, where two examplesof selected sequences are displayed graphically thereunder.

[0045]FIG. 14 is a three dimensional graph demonstrating the grouping ofsample molecular weight according to species.

[0046]FIG. 15 is a three dimensional graph demonstrating the grouping ofsample molecular weights according to species of virus and mammalinfected.

[0047]FIG. 16 is a three dimensional graph demonstrating the grouping ofsample molecular weights according to species of virus, andanimal-origin of infectious agent.

[0048]FIG. 17 is a figure depicting how the triangulation method of thepresent invention provides for the identification of an unknown bioagentwithout prior knowledge of the unknown agent. The use of differentprimer sets to distinguish and identify the unknown is also depicted asprimer sets I, II and III within this figure. A three dimensional graphdepicts all of bioagent space (170), including the unknown bioagent,which after use of primer set I (171) according to a method according tothe present invention further differentiates and classifies bioagentsaccording to major classifications (176) which, upon further analysisusing primer set II (172) differentiates the unknown agent (177) fromother, known agents (173) and finally, the use of a third primer set(175) further specifies subgroups within the family of the unknown(174).

DESCRIPTION OF PREFERRED EMBODIMENTS

[0049] The present invention provides a combination of a non-PCR biomassdetection mode, preferably high-resolution MS, with PCR-based BCStechnology using “intelligent primers” which hybridize to conservedsequence regions of nucleic-acids derived from a bioagent and whichbracket variable sequence regions that uniquely identify the bioagent.The high-resolution MS technique is used to determine the molecular massand base composition signature (BCS) of the amplified sequence region.This unique “base composition signature” (BCS) is then input to amaximum-likelihood detection algorithm for matching against a databaseof base composition signatures in the same amplified region. The presentmethod combines PCR-based amplification technology (which providesspecificity) and a molecular mass detection mode (which provides speedand does not require nucleic acid sequencing of the amplified targetsequence) for bioagent detection and identification.

[0050] The present method allows extremely rapid and accurate detectionand identification of bioagents compared to existing methods.Furthermore, this rapid detection and identification is possible evenwhen sample material is impure. The method leverages ongoing biomedicalresearch in virulence, pathogenicity, drug resistance and genomesequencing into a method which provides greatly improved sensitivity,specificity and reliability compared to existing methods, with lowerrates of false positives. Thus, the methods are useful in a wide varietyof fields, including, but not limited to, those fields discussed below.

[0051] In some embodiments of the invention, the methods disclosedherein can be used for environmental testing. Detection anddiscrimination of pathogenic vs. non-pathogenic bacteria, viruses,parasites, fungi and the like, in samples of water, land, air, or othersamples, can be carried out. Water samples can be obtained from, forexample, lakes, rivers, oceans, streams, water treatment systems,rainwater, groundwater, water table, reservoirs, wells, bottled water,and the like. Air samples can be obtained from ventilation systems,airplane cabins, schools, hospitals, mass transit locations such assubways, train stations, airports, and the like. Land samples can beobtained from any location.

[0052] In other embodiments of the invention, the methods disclosedherein can be used to screen blood and other bodily fluids and tissuesfor pathogenic and non-pathogenic bacteria, viruses, parasites, fungiand the like. Animal samples, including but not limited to, blood andother bodily fluid and tissue samples, can be obtained from livinganimals, who are either known or not known to or suspected of having adisease, infection, or condition. Alternately, animal samples such asblood and other bodily fluid and tissue samples can be obtained fromdeceased animals. Blood samples can be further separated into plasma orcellular fractions and further screened as desired. Bodily fluids andtissues can be obtained from any part of the animal or human body.Animal samples can be obtained from, for example, mammals and humans.

[0053] In other embodiments of the invention, the methods disclosedherein can be used for forensics. For example, medical examiners can usethe present invention to determine the cause of death. In addition,epidemiologists, for example, can use the present methods to determinethe geographic origin of a particular strain of bacteria or virus. Forexample, a particular strain of bacteria or virus may have a sequencedifference that is associated with a particular area of a country or theworld and identification of such a sequence difference can lead to theidentification of the geographic origin and epidemiological tracking ofthe spread of the particular disease, disorder or condition associatedwith the detected virus or bacteria. In addition, carriers of particularDNA or diseases, such as mammals, non-mammals, birds, insects, andplants, can be tracked by screening SNPs, VNTRs, or polyA, for example.Diseases, such as malaria, can be tracked by screening commensals, suchas mosquitos.

[0054] In other embodiments of the invention, the methods disclosedherein can be used for detecting the presence of pathogenic andnon-pathogenic bacteria, viruses, parasites, fungi and the like insamples of foodstuff or cosmetics. For example, food and wine can beexamined for the presence of pathogenic and non-pathogenic bacteria,viruses, parasites, fungi and the like. Particular types of foodssusceptible to bioagent contamination, such as agricultural products,meat products and eggs, can be examined for pathogenic organisms such asE. coli and Salmonella species. Such examination procedures can be usedby, for example, the wholesalers of foodstuffs and beverages, or byregulatory agencies such as the U.S. Department of Agriculture and theFood and Drug Administration. In addition, grapes and wines, forexample, can be examined using the present methods to detect particularstrains of bacteria or yeast that may indicate a particular time uponwhich to harvest the grapes or alter the wine-making process.

[0055] In other embodiments of the invention, the methods disclosedherein can be used for detecting the presence of bioagents in acontainer, such as a package, box, envelope, mail tube, railroad boxcar, and the like. For example, mail and package delivery entities andagencies, both domestic and abroad, as well investigative agencies suchas the FBI and ATF can use the present methods to detect bioagents incontainers.

[0056] In other embodiments of the invention, the methods disclosedherein can be used for detecting the presence of pathogenic andnon-pathogenic bacteria, viruses, parasites, fungi and. the like inorgan donors and/or in organs from donors. Such examination can resultin the prevention of the transfer of, for example, viruses such as WestNile virus, hepatitis viruses, human immunodeficiency virus, and thelike from a donor to a recipient via a transplanted organ. The methodsdisclosed herein can also be used for detection of host versus graft orgraft versus host rejection issues related to organ donors by detectingthe presence of particular antigens in either the graft or host known orsuspected of causing such rejection. In particular, the bioagents inthis regard are the antigens of the major histocompatibility complex,such as the HLA antigens.

[0057] In other embodiments of the invention, the methods disclosedherein can be used for detection and identification of livestockinfections such as, for example, mad cow disease, hoof and mouthdisease, and the like. Livestock includes, but is not limited to, cows,pigs, sheep, chickens, turkeys, goats, and other farm animals.

[0058] In other embodiments of the invention, the methods disclosedherein can be used for pharmacogenetic analysis and medical diagnosisincluding, but not limited to, cancer diagnosis based on mutations andpolymorphisms, drug resistance and susceptibility testing, screening forand/or diagnosis of genetic diseases and conditions, and diagnosis ofinfectious diseases and conditions. The present methods can also be usedto detect and track emerging infectious diseases, such as West Nilevirus infection, mad cow disease, and HIV-related diseases.

[0059] The present methods can be used to detect and classify anybiological agent, including bacteria, viruses, fungi and toxins. As oneexample, where the agent is a biological threat, the informationobtained is used to determine practical information needed forcountermeasures, including toxin genes, pathogenicity islands andantibiotic resistance genes. In addition, the methods can be used toidentify natural or deliberate engineering events including chromosomefragment swapping, molecular breeding (gene shuffling) and emerginginfectious diseases.

[0060] Bacteria have a common set of absolutely required genes. About250 genes are present in all bacterial species (Proc. Natl. Acad. Sci.U.S.A., 1996, 93, 10268; Science, 1995, 270, 397), including tinygenomes like Mycoplasma, Ureaplasma and Rickettsia. These genes encodeproteins involved in translation, replication, recombination and repair,transcription, nucleotide metabolism, amino acid metabolism, lipidmetabolism, energy generation, uptake, secretion and the like. Examplesof these proteins are DNA polymerase III beta, elongation factor TU,heat shock protein groEL, RNA polymerase beta, phosphoglycerate kinase,NADH dehydrogenase, DNA ligase, DNA topoisomerase and elongation factorG. Operons can also be targeted using the present method. One example ofan operon is the bfp operon from enteropathogenic E. coli. Multiple corechromosomal genes can be used to classify bacteria at a genus or genusspecies level to determine if an organism has threat potential. Themethods can also be used to detect pathogenicity markers (plasmid orchromosomal) and antibiotic resistance genes to confirm the threatpotential of an organism and to direct countermeasures.

[0061] A theoretically ideal bioagent detector would identify, quantify,and report the complete nucleic acid sequence of every bioagent thatreached the sensor. The complete sequence of the nucleic acid componentof a pathogen would provide all relevant information about the threat,including its identity and the presence of drug-resistance orpathogenicity markers. This ideal has not yet been achieved. However,the present invention provides a straightforward strategy for obtaininginformation with the same practical value using base compositionsignatures (BCS). While the base composition of a gene fragment is notas information-rich as the sequence itself, there is no need to analyzethe complete sequence of the gene if the short analyte sequence fragmentis properly chosen. A database of reference sequences can be prepared inwhich each sequence is indexed to a unique base composition signature,so that the presence of the sequence can be inferred with accuracy fromthe presence of the signature. The advantage of base compositionsignatures is that they can be quantitatively measured in a massivelyparallel fashion using multiplex PCR (PCR in which two or more primerpairs amplify target sequences simultaneously) and mass spectrometry.These multiple primer amplified regions uniquely identify most threatand ubiquitous background bacteria and viruses. In addition,cluster-specific primer pairs distinguish important local clusters(e.g., anthracis group).

[0062] In the context of this invention, a “bioagent” is any organism,living or dead, or a nucleic acid derived from such an organism.Examples of bioagents include but are not limited to cells (includingbut not limited to human clinical samples, bacterial cells and otherpathogens) viruses, parasites, fungi, toxin genes and bioregulatingcompounds. Samples may be alive or dead or in a vegetative state (forexample, vegetative bacteria or spores) and may be encapsulated orbioengineered.

[0063] As used herein, a “base composition signature” (BCS) is the exactbase composition from selected fragments of nucleic acid sequences thatuniquely identifies the target gene and source organism. BCS can bethought of as unique indexes of specific genes.

[0064] As used herein, “intelligent primers” are primers that bind tosequence regions that flank an intervening variable region. In apreferred embodiment, these sequence regions which flank the variableregion are highly conserved among different species of bioagent. Forexample, the sequence regions may be highly conserved among all Bacillusspecies. By the term “highly conserved,” it is meant that the sequenceregions exhibit between about 80-100%, more preferably between about90-100% and most preferably between about 95-100% identity. Examples ofintelligent primers that amplify regions of the 16S and 23S rRNA areshown in FIGS. 1A-1I. A typical primer amplified region in 16S rRNA isshown in FIG. 2. The arrows represent primers that bind to highlyconserved regions which flank a variable region in 16S rRNA domain III.The amplified region is the stem-loop structure under “1100-1188.”

[0065] One main advantage of the detection methods of the presentinvention is that the primers need not be specific for a particularbacterial species, or even genus, such as Bacillus or Streptomyces.Instead, the primers recognize highly conserved regions across hundredsof bacterial species including, but not limited to, the speciesdescribed herein. Thus, the same primer pair can be used to identify anydesired bacterium because it will bind to the conserved regions thatflank a variable region specific to a single species, or common toseveral bacterial species, allowing nucleic acid amplification of theintervening sequence and determination of its molecular weight and basecomposition. For example, the 16S_(—)971-1062, 16S_(—)1228-1310 and16S_(—)1100-1188 regions are 98-99% conserved in about 900 species ofbacteria (16S=16S rRNA, numbers indicate nucleotide position). In oneembodiment of the present invention, primers used in the present methodbind to one or more of these regions or portions thereof.

[0066] The present invention provides a combination of a non-PCR biomassdetection mode, preferably high-resolution MS, with nucleic acidamplification-based BCS technology using “intelligent primers” whichhybridize to conserved regions and which bracket variable regions thatuniquely identify the bioagent(s). Although the use of PCR is preferred,other nucleic acid amplification techniques may also be used, includingligase chain reaction (LCR) and strand displacement amplification (SDA).The high-resolution MS technique allows separation of bioagent spectrallines from background spectral lines in highly cluttered environments.The resolved spectral lines are then translated to BCS which are inputto a maximum-likelihood detection algorithm matched against spectra forone or more known BCS. Preferably, the bioagent BCS spectrum is matchedagainst one or more databases of BCS from vast numbers of bioagents.Preferably, the matching is done using a maximum-likelihood detectionalgorithm.

[0067] In one embodiment, base composition signatures are quantitativelymeasured in a massively parallel fashion using the polymerase chainreaction (PCR), preferably multiplex PCR, and mass spectrometric (MS)methods. Sufficient quantities of nucleic acids should be present fordetection of bioagents by MS. A wide variety of techniques for preparinglarge amounts of purified nucleic acids or fragments thereof are wellknown to those of skill in the art. PCR requires one or more pairs ofoligonucleotide primers that bind to regions which flank the targetsequence(s) to be amplified. These primers prime synthesis of adifferent strand of DNA, with synthesis occurring in the direction ofone primer towards the other primer. The primers, DNA to be amplified, athermostable DNA polymerase (e.g. Taq polymerase), the fourdeoxynucleotide triphosphates, and a buffer are combined to initiate DNAsynthesis. The solution is denatured by heating, then cooled to allowannealing of newly added primer, followed by another round of DNAsynthesis. This process is typically repeated for about 30 cycles,resulting in amplification of the target sequence.

[0068] The “intelligent primers” define the target sequence region to beamplified and analyzed. In one embodiment, the target sequence is aribosomal RNA (rRNA) gene sequence. With the complete sequences of manyof the smallest microbial genomes now available, it is possible toidentify a set of genes that defines “minimal life” and identifycomposition signatures that uniquely identify each gene and organism.Genes that encode core life functions such as DNA replication,transcription, ribosome structure, translation, and transport aredistributed broadly in the bacterial genome and are preferred regionsfor BCS analysis. Ribosomal RNA (rRNA) genes comprise regions thatprovide useful base composition signatures. Like many genes involved incore life functions, rRNA genes contain sequences that areextraordinarily conserved across bacterial domains interspersed withregions of high variability that are more specific to each species. Thevariable regions can be utilized to build a database of base compositionsignatures. The strategy involves creating a structure-based alignmentof sequences of the small (16S) and the large (23S) subunits of the rRNAgenes. For example, there are currently over 13,000 sequences in theribosomal RNA database that has been created and maintained by RobinGutell, University of Texas at Austin, and is publicly available on theInstitute for Cellular and Molecular Biology web page on the world wideweb of the Internet at, for example, “rna.icmb.utexas.edu/.” There isalso a publicly available rRNA database created and maintained by theUniversity of Antwerp, Belgium on the world wide web of the Internet at,for example, “rrna.uia.ac.be.” These databases have been analyzed todetermine regions that are useful as base composition signatures. Thecharacteristics of such regions include: a) between about 80 and 100%,preferably >about 95% identity among species of the particular bioagentof interest, of upstream and downstream nucleotide sequences which serveas sequence amplification primer sites; b) an intervening variableregion which exhibits no greater than about 5% identity among species;and c) a separation of between about 30 and 1000 nucleotides, preferablyno more than about 50-250 nucleotides, and more preferably no more thanabout 60-100 nucleotides, between the conserved regions.

[0069] Due to their overall conservation, the flanking rRNA primersequences serve as good “universal” primer binding sites to amplify theregion of interest for most, if not all, bacterial species. Theintervening region between the sets of primers varies in length and/orcomposition, and thus provides a unique base composition signature.

[0070] It is advantageous to design the “intelligent primers” to be asuniversal as possible to minimize the number of primers which need to besynthesized, and to allow detection of multiple species using a singlepair of primers. These primer pairs can be used to amplify variableregions in these species. Because any variation (due to codon wobble inthe 3^(rd) position) in these conserved regions among species is likelyto occur in the third position of a DNA triplet, oligonucleotide primerscan be designed such that the nucleotide corresponding to this positionis a base which can bind to more than one nucleotide, referred to hereinas a “universal base.” For example, under this “wobble” pairing, inosine(I) binds to U, C or A; guanine (G) binds to U or C, and uridine (U)binds to U or C. Other examples of universal bases include nitroindolessuch as 5-nitroindole or 3-nitropyrrole (Loakes et al., Nucleosides andNucleotides, 1995, 14, 1001-1003), the degenerate nucleotides dP or dK(Hill et al.), an acyclic nucleoside analog containing 5-nitroindazole(Van Aerschot et al., Nucleosides and Nucleotides, 1995, 14, 1053-1056)or the purine analog1-(2-deoxy-β-D-ribofuranosyl)-imidazole-4-carboxamide (Sala et al.,Nucl. Acids Res., 1996, 24, 3302-3306).

[0071] In another embodiment of the invention, to compensate for thesomewhat weaker binding by the “wobble” base, the oligonucleotideprimers are designed such that the first and second positions of eachtriplet are occupied by nucleotide analogs which bind with greateraffinity than the unmodified nucleotide. Examples of these analogsinclude, but are not limited to, 2,6-diaminopurine which binds tothymine, propyne T which binds to adenine and propyne C andphenoxazines, including G-clamp, which binds to G. Propynes aredescribed in U.S. Pat. Nos. 5,645,985, 5,830.653 and 5,484,908, each ofwhich is incorporated herein by reference in its entirety. Phenoxazinesare described in U.S. Pat. Nos. 5,502,177, 5,763,588, and 6,005,096,each of which is incorporated herein by reference in its entirety.G-clamps are described in U.S. Pat. Nos. 6,007,992 and 6,028,183, eachof which is incorporated herein by reference in its entirety.

[0072] Bacterial biological warfare agents capable of being detected bythe present methods include, but are not limited to, Bacillus anthracis(anthrax), Yersinia pestis (pneumonic plague), Franciscella tularensis(tularemia), Brucella suis, Brucella abortus, Brucella melitensis(undulant fever), Burkholderia mallei (glanders), Burkholderiapseudomalleii (melioidosis), Salmonella typhi (typhoid fever),Rickettsia typhii (epidemic typhus), Rickettsia prowasekii (endemictyphus) and Coxiella burnetii (Q fever), Rhodobacter capsulatus,Chlamydia pneumoniae, Escherichia coli, Shigella dysenteriae, Shigellaflexneri, Bacillus cereus, Clostridium botulinum, Coxiella burnetti,Pseudomonas aeruginosa, Legionella pneumophila, and Vibrio cholerae.

[0073] Besides 16S and 23S rRNA, other target regions suitable for usein the present invention for detection of bacteria include, but are notlimited to, 5S rRNA and RNase P (FIG. 3).

[0074] Biological warfare fungus biowarfare agents include, but are notlimited to, coccidioides immitis (Coccidioidomycosis).

[0075] Biological warfare toxin genes capable of being detected by themethods of the present invention include, but are not limited to,botulism, T-2 mycotoxins, ricin, staph enterotoxin B, shigatoxin, abrin,aflatoxin, Clostridium perfringens epsilon toxin, conotoxins,diacetoxyscirpenol, tetrodotoxin and saxitoxin.

[0076] Biological warfare viral threat agents are mostly RNA viruses(positive-strand and negative-strand), with the exception of smallpox.Every RNA virus is a family of related viruses (quasispecies). Theseviruses mutate rapidly and the potential for engineered strains (naturalor deliberate) is very high. RNA viruses cluster into families that haveconserved RNA structural domains on the viral genome (e.g., virioncomponents, accessory proteins) and conserved housekeeping genes thatencode core viral proteins including, for single strand positive strandRNA viruses, RNA-dependent RNA polymerase, double stranded RNA helicase,chymotrypsin-like and papain-like proteases and methyltransferases.

[0077] Examples of (−)-strand RNA viruses include, but are not limitedto, arenaviruses (e.g., sabia virus, lassa fever, Machupo, Argentinehemorrhagic fever, flexal virus), bunyaviruses (e.g., hantavirus,nairovirus, phlebovirus, hantaan virus, Congo-crimean hemorrhagic fever,rift valley fever), and mononegavirales (e.g., filovirus, paramyxovirus,ebola virus, Marburg, equine morbillivirus).

[0078] Examples of (+)-strand RNA viruses include, but are not limitedto, picomaviruses (e.g., coxsackievirus, echovirus, human coxsackievirusA, human echovirus, human enterovirus, human poliovirus, hepatitis Avirus, human parechovirus, human rhinovirus), astroviruses (e.g., humanastrovirus), calciviruses (e.g., chiba virus, chitta virus, humancalcivirus, norwalk virus), nidovirales (e.g., human coronavirus, humantorovirus), flaviviruses (e.g., dengue virus 1-4, Japanese encephalitisvirus, Kyanasur forest disease virus, Murray Valley encephalitis virus,Rocio virus, St. Louis encephalitis virus, West Nile virus, yellow fevervirus, hepatitis c virus) and togaviruses (e.g., Chikugunya virus,Eastern equine encephalitis virus, Mayaro virus, O'nyong-nyong virus,Ross River virus, Venezuelan equine encephalitis virus, Rubella virus,hepatitis E virus). The hepatitis C virus has a 5′-untranslated regionof 340 nucleotides, an open reading frame encoding 9 proteins having3010 amino acids and a 3′-untranslated region of 240 nucleotides. The5′-UTR and 3′-UTR are 99% conserved in hepatitis C viruses.

[0079] In one embodiment, the target gene is an RNA-dependent RNApolymerase or a helicase encoded by (+)-strand RNA viruses, or RNApolymerase from a (−)-strand RNA virus. (+)-strand RNA viruses aredouble stranded RNA and replicate by RNA-directed RNA synthesis usingRNA-dependent RNA polymerase and the positive strand as a template.Helicase unwinds the RNA duplex to allow replication of the singlestranded RNA. These viruses include viruses from the familypicomaviridae (e.g., poliovirus, coxsackievirus, echovirus), togaviridae(e.g., alphavirus, flavivirus, rubivirus), arenaviridae (e.g.,lymphocytic choriomeningitis virus, lassa fever virus), cononaviridae(e.g., human respiratory virus) and Hepatitis A virus. The genesencoding these proteins comprise variable and highly conserved regionswhich flank the variable regions.

[0080] In another embodiment, the detection scheme for the PCR productsgenerated from the bioagent(s) incorporates at least three features.First, the technique simultaneously detects and differentiates multiple(generally about 6-10) PCR products. Second, the technique provides aBCS that uniquely identifies the bioagent from the possible primersites. Finally, the detection technique is rapid, allowing multiple PCRreactions to be run in parallel.

[0081] In one embodiment, the method can be used to detect the presenceof antibiotic resistance and/or toxin genes in a bacterial species. Forexample, Bacillus anthracis comprising a tetracycline resistance plasmidand plasmids encoding one or both anthracis toxins (px01 and/or px02)can be detected by using antibiotic resistance primer sets and toxingene primer sets. If the B. anthracis is positive for tetracyclineresistance, then a different antibiotic, for example quinalone, is used.

[0082] Mass spectrometry (MS)-based detection of PCR products providesall of these features with additional advantages. MS is intrinsically aparallel detection scheme without the need for radioactive orfluorescent labels, since every amplification product with a unique basecomposition is identified by its molecular mass. The current state ofthe art in mass spectrometry is such that less than femtomole quantitiesof material can be readily analyzed to afford information about themolecular contents of the sample. An accurate assessment of themolecular mass of the material can be quickly obtained, irrespective ofwhether the molecular weight of the sample is several hundred, or inexcess of one hundred thousand atomic mass units (amu) or Daltons.Intact molecular ions can be generated from amplification products usingone of a variety of ionization techniques to convert the sample to gasphase. These ionization methods include, but are not limited to,electrospray ionization (ES), matrix-assisted laser desorptionionization (MALDI) and fast atom bombardment (FAB). For example, MALDIof nucleic acids, along with examples of matrices for use in MALDI ofnucleic acids, are described in WO 98/54751 (Genetrace, Inc.).

[0083] In some embodiments, large DNAs and RNAs, or large amplificationproducts therefrom, can be digested with restriction endonucleases priorto ionization. Thus, for example, an amplification product that was 10kDa could be digested with a series of restriction endonucleases toproduce a panel of, for example, 100 Da fragments. Restrictionendonucleases and their sites of action are well known to the skilledartisan. In this manner, mass spectrometry can be performed for thepurposes of restriction mapping.

[0084] Upon ionization, several peaks are observed from one sample dueto the formation of ions with different charges. Averaging the multiplereadings of molecular mass obtained from a single mass spectrum affordsan estimate of molecular mass of the bioagent. Electrospray ionizationmass spectrometry (ESI-MS) is particularly useful for very highmolecular weight polymers such as proteins and nucleic acids havingmolecular weights greater than 10 kDa, since it yields a distribution ofmultiply-charged molecules of the sample without causing a significantamount of fragmentation.

[0085] The mass detectors used in the methods of the present inventioninclude, but are not limited to, Fourier transform ion cyclotronresonance mass spectrometry (FT-ICR-MS), ion trap, quadrupole, magneticsector, time of flight (TOF), Q-TOF, and triple quadrupole.

[0086] In general, the mass spectrometric techniques which can be usedin the present invention include, but are not limited to, tandem massspectrometry, infrared multiphoton dissociation and pyrolytic gaschromatography mass spectrometry (PGC-MS). In one embodiment of theinvention, the bioagent detection system operates continually inbioagent detection mode using pyrolytic GC-MS without PCR for rapiddetection of increases in biomass (for example, increases in fecalcontamination of drinking water or of germ warfare agents). To achieveminimal latency, a continuous sample stream flows directly into thePGC-MS combustion chamber. When an increase in biomass is detected, aPCR process is automatically initiated. Bioagent presence produceselevated levels of large molecular fragments from, for example, about100-7,000 Da which are observed in the PGC-MS spectrum. The observedmass spectrum is compared to a threshold level and when levels ofbiomass are determined to exceed a predetermined threshold, the bioagentclassification process described hereinabove (combining PCR and MS,preferably FT-ICR MS) is initiated. Optionally, alarms or otherprocesses (halting ventilation flow, physical isolation) are alsoinitiated by this detected biomass level.

[0087] The accurate measurement of molecular mass for large DNAs islimited by the adduction of cations from the PCR reaction to eachstrand, resolution of the isotopic peaks from natural abundance ¹³C and¹⁵N isotopes, and assignment of the charge state for any ion. Thecations are removed by in-line dialysis using a flow-through chip thatbrings the solution containing the PCR products into contact with asolution containing ammonium acetate in the presence of an electricfield gradient orthogonal to the flow. The latter two problems areaddressed by operating with a resolving power of >100,000 and byincorporating isotopically depleted nucleotide triphosphates into theDNA. The resolving power of the instrument is also a consideration. At aresolving power of 10,000, the modeled signal from the [M-14H+]¹⁴⁻charge state of an 84mer PCR product is poorly characterized andassignment of the charge state or exact mass is impossible. At aresolving power of 33,000, the peaks from the individual isotopiccomponents are visible. At a resolving power of 100,000, the isotopicpeaks are resolved to the baseline and assignment of the charge statefor the ion is straightforward. The [¹³C, ¹⁵N]-depleted triphosphatesare obtained, for example, by growing microorganisms on depleted mediaand harvesting the nucleotides (Batey et al., Nucl. Acids Res., 1992,20, 4515-4523).

[0088] While mass measurements of intact nucleic acid regions arebelieved to be adequate to determine most bioagents, tandem massspectrometry (MS^(n)) techniques may provide more definitive informationpertaining to molecular identity or sequence. Tandem MS involves thecoupled use of two or more stages of mass analysis where both theseparation and detection steps are based on mass spectrometry. The firststage is used to select an ion or component of a sample from whichfurther structural information is to be obtained. The selected ion isthen fragmented using, e.g., blackbody irradiation, infrared multiphotondissociation, or collisional activation. For example, ions generated byelectrospray ionization (ESI) can be fragmented using IR multiphotondissociation. This activation leads to dissociation of glycosidic bondsand the phosphate backbone, producing two series of fragment ions,called the w-series (having an intact 3′ terminus and a 5′ phosphatefollowing internal cleavage) and the a-Base series (having an intact 5′terminus and a 3′ furan).

[0089] The second stage of mass analysis is then used to detect andmeasure the mass of these resulting fragments of product ions. Such ionselection followed by fragmentation routines can be performed multipletimes so as to essentially completely dissect the molecular sequence ofa sample.

[0090] If there are two or more targets of similar base composition ormass, or if a single amplification reaction results in a product whichhas the same mass as two or more bioagent reference standards, they canbe distinguished by using mass-modifying “tags.” In this embodiment ofthe invention, a nucleotide analog or “tag” is incorporated duringamplification (e.g., a 5-(trifluoromethyl) deoxythymidine triphosphate)which has a different molecular weight than the unmodified base so as toimprove distinction of masses. Such tags are described in, for example,PCT WO97/33000, which is incorporated herein by reference in itsentirety. This further limits the number of possible base compositionsconsistent with any mass. For example, 5-(trifluoromethyl)deoxythymidinetriphosphate can be used in place of dTTP in a separate nucleic acidamplification reaction. Measurement of the mass shift between aconventional amplification product and the tagged product is used toquantitate the number of thymidine nucleotides in each of the singlestrands. Because the strands are complementary, the number of adenosinenucleotides in each strand is also determined.

[0091] In another amplification reaction, the number of G and C residuesin each strand is determined using, for example, the cytidine analog5-methylcytosine (5-meC) or propyne C. The combination of the A/Treaction and G/C reaction, followed by molecular weight determination,provides a unique base composition. This method is summarized in FIG. 4and Table 1. TABLE 1 Total Total Total Base Base base base mass infoinfo comp. comp. Double strand Single strand this this other Top BottomMass tag sequence Sequence strand strand strand strand strand T*massT*ACGT*AC T*ACGT*AC 3x 3T 3A 3T 3A (T*-T)=x GT* GT* 2A 2T AT*GCAT*G 2C2G CA 2G 2C AT*GCAT*G 2x 2T 2A CA C*mass TAC*GTAC* TAC*GTAC* 2x 2C 2G(C*-C)=y GT GT ATGC*ATGC *A ATGC*ATGC 2x 2C 2G *A

[0092] The mass tag phosphorothioate A (A*) was used to distinguish aBacillus anthracis cluster. The B. anthracis (A₁₄G₉C₁₄T₉) had an averageMW of 14072.26, and the B. anthracis (A₁A*₁₃G₉C₁₄T₉) had an averagemolecular weight of 14281.11 and the phosphorothioate A had an averagemolecular weight of +16.06 as determined by ESI-TOF MS. The deconvolutedspectra are shown in FIG. 5.

[0093] In another example, assume the measured molecular masses of eachstrand are 30,000.115Da and 31,000.115 Da respectively, and the measurednumber of dT and dA residues are (30,28) and (28,30). If the molecularmass is accurate to 100 ppm, there are 7 possible combinations of dG+dCpossible for each strand. However, if the measured molecular mass isaccurate to 10 ppm, there are only 2 combinations of dG+dC, and at 1 ppmaccuracy there is only one possible base composition for each strand.

[0094] Signals from the mass spectrometer may be input to amaximum-likelihood detection and classification algorithm such as iswidely used in radar signal processing. The detection processing usesmatched filtering of BCS observed in mass-basecount space and allows fordetection and subtraction of signatures from known, harmless organisms,and for detection of unknown bioagent threats. Comparison of newlyobserved bioagents to known bioagents is also possible, for estimationof threat level, by comparing their BCS to those of known organisms andto known forms of pathogenicity enhancement, such as insertion ofantibiotic resistance genes or toxin genes.

[0095] Processing may end with a Bayesian classifier using loglikelihood ratios developed from the observed signals and averagebackground levels. The program emphasizes performance predictionsculminating in probability-of-detection versusprobability-of-false-alarm plots for conditions involving complexbackgrounds of naturally occurring organisms and environmentalcontaminants. Matched filters consist of a priori expectations of signalvalues given the set of primers used for each of the bioagents. Agenomic sequence database (e.g. GenBank) is used to define the massbasecount matched filters. The database contains known threat agents andbenign background organisms. The latter is used to estimate and subtractthe signature produced by the background organisms. A maximum likelihooddetection of known background organisms is implemented using matchedfilters and a running-sum estimate of the noise covariance. Backgroundsignal strengths are estimated and used along with the matched filtersto form signatures which are then subtracted. the maximum likelihoodprocess is applied to this “cleaned up” data in a similar manneremploying matched filters for the organisms and a running-sum estimateof the noise-covariance for the cleaned up data.

[0096] In one embodiment, a strategy to “triangulate” each organism bymeasuring signals from multiple core genes is used to reduce falsenegative and false positive signals, and enable reconstruction of theorigin or hybrid or otherwise engineered bioagents. After identificationof multiple core genes, alignments are created from nucleic acidsequence databases. The alignments are then analyzed for regions ofconservation and variation, and potential primer binding sites flankingvariable regions are identified. Next, amplification target regions forsignature analysis are selected which distinguishes organisms based onspecific genomic differences (i.e., base composition). For example,detection of signatures for the three part toxin genes typical of B.anthracis (Bowen et al., J. Appl. Microbiol., 1999, 87, 270-278) in theabsence of the expected signatures from the B. anthracis genome wouldsuggest a genetic engineering event.

[0097] The present method can also be used to detect single nucleotidepolymorphisms (SNPs), or multiple nucleotide polymorphisms, rapidly andaccurately. A SNP is defined as a single base pair site in the genomethat is different from one individual to another. The difference can beexpressed either as a deletion, an insertion or a substitution, and isfrequently linked to a disease state. Because they occur every 100-1000base pairs, SNPs are the most frequently bound type of genetic marker inthe human genome.

[0098] For example, sickle cell anemia results from an A-T transition,which encodes a valine rather than a glutamic acid residue.Oligonucleotide primers may be designed such that they bind to sequencesthat flank a SNP site, followed by nucleotide amplification and massdetermination of the amplified product. Because the molecular masses ofthe resulting product from an individual who does not have sickle cellanemia is different from that of the product from an individual who hasthe disease, the method can be used to distinguish the two individuals.Thus, the method can be used to detect any known SNP in an individualand thus diagnose or determine increased susceptibility to a disease orcondition.

[0099] In one embodiment, blood is drawn from an individual andperipheral blood mononuclear cells (PBMC) are isolated andsimultaneously tested, preferably in a high-throughput screening method,for one or more SNPs using appropriate primers based on the knownsequences which flank the SNP region. The National Center forBiotechnology Information maintains a publicly available database ofSNPs on the world wide web of the Internet at, for example,“ncbi.nlm.nih.gov/SNP/.”

[0100] The method of the present invention can also be used for bloodtyping. The gene encoding A, B or O blood type can differ by four singlenucleotide polymorphisms. If the gene contains the sequenceCGTGGTGACCCTT (SEQ ID NO:5), antigen A results. If the gene contains thesequence CGTCGTCACCGCTA (SEQ ID NO:6) antigen B results. If the genecontains the sequence CGTGGT-ACCCCTT (SEQ ID NO:7), blood group Oresults (“−” indicates a deletion). These sequences can be distinguishedby designing a single primer pair which flanks these regions, followedby amplification and mass determination.

[0101] While the present invention has been described with specificityin accordance with certain of its preferred embodiments, the followingexamples serve only to illustrate the invention and are not intended tolimit the same.

EXAMPLES Example 1 Nucleic Acid Isolation and PCR

[0102] In one embodiment, nucleic acid is isolated from the organismsand amplified by PCR using standard methods prior to BCS determinationby mass spectrometry. Nucleic acid is isolated, for example, bydetergent lysis of bacterial cells, centrifugation and ethanolprecipitation. Nucleic acid isolation methods are described in, forexample, Current Protocols in Molecular Biology (Ausubel et al.) andMolecular Cloning; A Laboratory Manual (Sambrook et al.). The nucleicacid is then amplified using standard methodology, such as PCR, withprimers which bind to conserved regions of the nucleic acid whichcontain an intervening variable sequence as described below.

Example 2 Mass Spectrometry

[0103] FTICR Instrumentation: The FTICR instrument is based on a 7 teslaactively shielded superconducting magnet and modified Bruker DaltonicsApex II 70e ion optics and vacuum chamber. The spectrometer isinterfaced to a LEAP PAL autosampler and a custom fluidics controlsystem for high throughput screening applications. Samples are analyzeddirectly from 96-well or 384-well microtiter plates at a rate of about 1sample/minute. The Bruker data-acquisition platform is supplemented witha lab-built ancillary NT datastation which controls the autosampler andcontains an arbitrary waveform generator capable of generating complexrf-excite waveforms (frequency sweeps, filtered noise, stored waveforminverse Fourier transform (SWIFT), etc.) for sophisticated tandem MSexperiments. For oligonucleotides in the 20-30-mer regime typicalperformance characteristics include mass resolving power in excess of100,000 (FWHM), low ppm mass measurement errors, and an operable m/zrange between 50 and 5000 m/z.

[0104] Modified ESI Source: In sample-limited analyses, analytesolutions are delivered at 150 nL/minute to a 30 mm i.d. fused-silicaESI emitter mounted on a 3-D micromanipulator. The ESI ion opticsconsists of a heated metal capillary, an rf-only hexapole, a skimmercone, and an auxiliary gate electrode. The 6.2 cm rf-only hexapole iscomprised of 1 mm diameter rods and is operated at a voltage of 380 Vppat a frequency of 5 MHz. A lab-built electro-mechanical shutter can beemployed to prevent the electrospray plume from entering the inletcapillary unless triggered to the “open” position via a TTL pulse fromthe data station. When in the “closed” position, a stable electrosprayplume is maintained between the ESI emitter and the face of the shutter.The back face of the shutter arm contains an elastomeric seal that canbe positioned to form a vacuum seal with the inlet capillary. When theseal is removed, a 1 mm gap between the shutter blade and the capillaryinlet allows constant pressure in the external ion reservoir regardlessof whether the shutter is in the open or closed position. When theshutter is triggered, a “time slice” of ions is allowed to enter theinlet capillary and is subsequently accumulated in the external ionreservoir. The rapid response time of the ion shutter (<25 ms) providesreproducible, user defined intervals during which ions can be injectedinto and accumulated in the external ion reservoir.

[0105] Apparatus for Infrared Multiphoton Dissociation A 25 watt CW CO₂laser operating at 10.6 μm has been interfaced to the spectrometer toenable infrared multiphoton dissociation (IRMPD) for oligonucleotidesequencing and other tandem MS applications. An aluminum optical benchis positioned approximately 1.5 m from the actively shieldedsuperconducting magnet such that the laser beam is aligned with thecentral axis of the magnet. Using standard IR-compatible mirrors andkinematic mirror mounts, the unfocused 3 mm laser beam is aligned totraverse directly through the 3.5 mm holes in the trapping electrodes ofthe FTICR trapped ion cell and longitudinally traverse the hexapoleregion of the external ion guide finally impinging on the skimmer cone.This scheme allows IRMPD to be conducted in an m/z selective manner inthe trapped ion cell (e.g. following a SWIFT isolation of the species ofinterest), or in a broadband mode in the high pressure region of theexternal ion reservoir where collisions with neutral molecules stabilizeIRMPD-generated metastable fragment ions resulting in increased fragmention yield and sequence coverage.

Example 3 Identification of Bioagents

[0106] Table 2 shows a small cross section of a database of calculatedmolecular masses for over 9 primer sets and approximately 30 organisms.The primer sets were derived from rRNA alignment. Examples of regionsfrom rRNA consensus alignments are shown in FIGS. 1A-1C. Lines witharrows are examples of regions to which intelligent primer pairs for PCRare designed. The primer pairs are >95% conserved in the bacterialsequence database (currently over 10,000 organisms). The interveningregions are variable in length and/or composition, thus providing thebase composition “signature” (BCS) for each organism. Primer pairs werechosen so the total length of the amplified region is less than about80-90 nucleotides. The label for each primer pair represents thestarting and ending base number of the amplified region on the consensusdiagram.

[0107] Included in the short bacterial database cross-section in Table 2are many well known pathogens/biowarfare agents (shown in bold/redtypeface) such as Bacillus anthracis or Yersinia pestis as well as someof the bacterial organisms found commonly in the natural environmentsuch as Streptomyces. Even closely related organisms can bedistinguished from each other by the appropriate choice of primers. Forinstance, two low G+C organisms, Bacillus anthracis and Staph aureus,can be distinguished from each other by using the primer pair defined by16S_(—)1337 or 23S_(—)855 (ΔM of 4 Da). TABLE 2 Cross Section Of ADatabase Of Calculated Molecular Masses¹ Primer Regions----> Bug Name16S_971 16S_1100 16S_1337 16S_1294 16S_1228 23S_1021 23S_855 23S_19323S_115 Acinetobacter calcoaceticus 55619.1 55004 28446.7 35854.951295.4 30299 42654 39557.5 54999 Bacillus anthracis 55005 54388 2844835238 51296 30295 42651 39560 56850 Bacillus cereus 55622.1 54387.928447.6 35854.9 51296.4 30295 42651 39560.5 56850.3 Bordetellabronchiseptica 56857.3 51300.4 28446.7 35857.9 51307.4 30299 4265339559.5 51920.5 Borrelia burgdorferi 56231.2 55621.1 28440.7 35852.951295.4 30297 42029.9 38941.4 52524.6 Brucella abortus 58098 55011 2844835854 50683 Campylobacter jejuni 58088.5 54386.9 29061.8 35856.9 50674.330294 42032.9 39558.5 45732.5 Chlamydia pnuemoniae 55000 55007 2906335855 50676 30295 42036 38941 56230 Clostridium botulinum 55006 5376728445 35855 51291 30300 42656 39562 54999 Clostridium difficile 56855.354386.9 28444.7 35853.9 51296.4 30294 41417.8 39556.5 55612.2Enterococcus faecalis 55620.1 54387.9 28447.6 35858.9 51296.4 3029742652 39559.5 56849.3 Escherichia coli 55622 55009 28445 35857 5130130301 42656 39562 54999 Francisella tularensis 53769 54385 28445 3585651298 Haemophilus influenzae 55620.1 55006 28444.7 35855.9 51298.4 3029842656 39560.5 55613.1 Klebsiella pneumoniae 55622.1 55008 28442.735856.9 51297.4 30300 42655 39562.5 55000 Legionella pneumophila 5561855626 28446 35857 51303 Mycobacterium avium 54390.9 55631.1 29064.835858.9 51915.5 30296 42656 38942.4 56241.2 Mycobacterium leprae 54389.955629.1 29064.8 35860.9 51917.5 30298 42656 39559.5 56240.2Mycobacterium tuberculosis 54390.9 55629.1 29064.8 35860.9 51301.4 3029942656 39560.5 56243.2 Mycoplasma genitalium 53143.7 45115.4 29061.835854.9 50671.3 30294 43264.1 39558.5 56842.4 Mycoplasma pneumoniae53143.7 45115.4 29061.8 35854.9 50671.3 30294 43264.1 39558.5 56842.4Neisseria gonorrhoeae 55627.1 54389.9 28445.7 35855.9 51302.4 3030042649 39561.5 55000 Pseudomonas aeruginosa 55623 55010 28443 35858 5130130298 43272 39558 55619 Rickettsia prowazekii 58093 55621 28448 3585350677 30293 42650 39559 53139 Rickettsia rickettsii 58094 55623 2844835853 50679 30293 42648 39559 53755 Salmonella typhimurium 55622 5500528445 35857 51301 30301 42658 Shigella dysenteriae 55623 55009 2844435857 51301 Staphylococcus aureus 56854.3 54386.9 28443.7 35852.951294.4 30298 42655 39559.5 57466.4 Streptomyces 54389.9 59341.6 29063.835858.9 51300.4 39563.5 56864.3 Treponema pallidum 56245.2 55631.128445.7 35851.9 51297.4 30299 42034.9 38939.4 57473.4 Vibrio cholerae55625 55626 28443 35857 52536 29063 30303 35241 50675 Vibrioparahaemolyticus 54384.9 55626.1 28444.7 34620.7 50064.2 Yersinia pestis55620 55626 28443 35857 51299

[0108]FIG. 6 shows the use of ESI-FT-ICR MS for measurement of exactmass. The spectra from 46mer PCR products originating at position 1337of the 16S rRNA from S. aureus (upper) and B. anthracis (lower) areshown. These data are from the region of the spectrum containing signalsfrom the [M-8H+]⁸⁻ charge states of the respective 5′-3′ strands. Thetwo strands differ by two (AT→CG) substitutions, and have measuredmasses of 14206.396 and 14208.373±0.010 Da, respectively. The possiblebase compositions derived from the masses of the forward and reversestrands for the B. anthracis products are listed in Table 3. TABLE 3Possible base composition for B. anthracis products Calc. Mass ErrorBase Comp. 14208.2935 0.079520 A1 G17 C10 T18 14208.3160 0.056980 A1 G20C15 T10 14208.3386 0.034440 A1 G23 C20 T2 14208.3074 0.065560 A6 G11 C3T26 14208.3300 0.043020 A6 G14 C8 T18 14208.3525 0.020480 A6 G17 C13 T1014208.3751 0.002060 A6 G20 C18 T2 14208.3439 0.029060 A11 G8 C1 T2614208.3665 0.006520 A11 G11 C6 T18 14208.3890 0.016020 A11 G14 C11 T1014208.4116 0.038560 A11 G17 C16 T2 14208.4030 0.029980 A16 G8 C4 T1814208.4255 0.052520 A16 G11 C9 T10 14208.4481 0.075060 A16 G14 C14 T214208.4395 0.066480 A21 G5 C2 T18 14208.4620 0.089020 A21 G8 C7 T1014079.2624 0.080600 A0 G14 C13 T19 14079.2849 0.058060 A0 G17 C18 T1114079.3075 0.035520 A0 G20 C23 T3 14079.2538 0.089180 A5 G5 C1 T3514079.2764 0.066640 A5 G8 C6 T27 14079.2989 0.044100 A5 G11 C11 T1914079.3214 0.021560 A5 G14 C16 T11 14079.3440 0.000980 A5 G17 C21 T314079.3129 0.030140 A10 G5 C4 T27 14079.3354 0.007600 A10 G8 C9 T1914079.3579 0.014940 A10 G11 C14 T11 14079.3805 0.037480 A10 G14 C19 T314079.3494 0.006360 A15 G2 C2 T27 14079.3719 0.028900 A15 G5 C7 T1914079.3944 0.051440 A15 G8 C12 T11 14079.4170 0.073980 A15 G11 C17 T314079.4084 0.065400 A20 G2 C5 T19 14079.4309 0.087940 A20 G5 C10 T13

[0109] Among the 16 compositions for the forward strand and the 18compositions for the reverse strand that were calculated, only one pair(shown in bold) are complementary, corresponding to the actual basecompositions of the B. anthracis PCR products.

Example 4 BCS of Region from Bacillus anthracis and Bacillus cereus

[0110] A conserved Bacillus region from B. anthracis (A₁₄G₉C₁₄T₉) and B.cereus (A₁₅G₉C₁₃T₉) having a C to A base change was synthesized andsubjected to ESI-TOF MS. The results are shown in FIG. 7 in which thetwo regions are clearly distinguished using the method of the presentinvention (MW=14072.26 vs. 14096.29).

Example 5 Identification of Additional Bioagents

[0111] In other examples of the present invention, the pathogen Vibriocholera can be distinguished from Vibrio parahemolyticus with ΔM>600 Dausing one of three 16S primer sets shown in Table 2 (16S_(—)971,16S_(—)1228 or 16S_(—)1294) as shown in Table 4. The two mycoplasmaspecies in the list (M. genitalium and M. pneumoniae) can also bedistinguished from each other, as can the three mycobacteriae. While thedirect mass measurements of amplified products can identify anddistinguish a large number of organisms, measurement of the basecomposition signature provides dramatically enhanced resolving power forclosely related organisms. In cases such as Bacillus anthracis andBacillus cereus that are virtually indistinguishable from each otherbased solely on mass differences, compositional analysis orfragmentation patterns are used to resolve the differences. The singlebase difference between the two organisms yields different fragmentationpatterns, and despite the presence of the ambiguous/unidentified base Nat position 20 in B. anthracis, the two organisms can be identified.

[0112] Tables 4a-b show examples of primer pairs from Table 1 whichdistinguish pathogens from background. TABLE 4a Organism name 23S_85516S_1337 23S_1021 Bacillus anthracis 42650.98 28447.65 30294.98Staphylococcus aureus 42654.97 28443.67 30297.96

[0113] TABLE 4b Organism name 16S_971 16S_1294 16S_1228 Vibrio cholerae55625.09 35856.87 52535.59 Vibrio parahaemolyticus 54384.91 34620.6750064.19

[0114] Table 4 shows the expected molecular weight and base compositionof region 16S_(—)1100-1188 in Mycobacterium avium and Streptomyces sp.TABLE 5 Molecular Region Organism name Length weight Base comp.16S_1100-1188 Mycobacterium avium 82 25624.1728 A₁₆G₃₂C₁₈T₁₆16S_1100-1188 Streptomyces sp. 96 29904.871  A₁₇G₃₈C₂₇T₁₄

[0115] Table 5 shows base composition (single strand) results for16S_(—)1100-1188 primer amplification reactions different species ofbacteria. Species which are repeated in the table (e.g., Clostridiumbotulinum) are different strains which have different base compositionsin the 16S_(—)1100-1188 region. TABLE 6 Organism name Base comp.Mycobacterium avium A₁₆G₃₂C₁₈T₁₆ Streptomyces sp. A₁₇G₃₈C₂₇T₁₄Ureaplasma urealyticum A₁₈G₃₀C₁₇T₁₇ Streptomyces sp. A₁₉G₃₆C₂₄T₁₈Mycobacterium leprae A₂₀G₃₂C₂₂T₁₆ M. tuberculosis A₂₀G₃₃C₂₁T₁₆ Nocardiaasteroides A₂₀G₃₃C₂₁T₁₆ Fusobacterium necroforum A₂₁G₂₆C₂₂T₁₈ Listeriamonocytogenes A₂₁G₂₇C₁₉T₁₉ Clostridium botulinum A₂₁G₂₇C₁₉T₂₁ Neisseriagonorrhoeae A₂₁G₂₈C₂₁T₁₈ Bartonella quintana A₂₁G₃₀C₂₂T₁₆ Enterococcusfaecalis A₂₂G₂₇C₂₀T₁₉ Bacillus megaterium A₂₂G₂₈C₂₀T₁₈ Bacillus subtilisA₂₂G₂₈C₂₁T₁₇ Pseudomonas aeruginosa A₂₂G₂₉C₂₃T_(I5) Legionellapneumophila A₂₂G₃₂C₂₀T₁₆ Mycoplasma pneumoniae A₂₃G₂₀C₁₄T₁₆ Clostridiumbotulinum A₂₃G₂₆C₂₀T₁₉ Enterococcus faecium A₂₃G₂₆C₂₁T₁₈ Acinetobactercalcoaceti A₂₃G₂₆C₂₁T₁₉ Leptospira borgpeterseni A₂₃G₂₆C₂₄T₁₅ Leptospirainterrogans A₂₃G₂₆C₂₄T₁₅ Clostridium perfringens A₂₃G₂₇C₁₉T₁₉ Bacillusanthracis A₂₃G₂₇C₂₀T₁₈ Bacillus cereus A₂₃G₂₇C₂₀T₁₈ Bacillusthuringiensis A₂₃G₂₇C₂₀T₁₈ Aeromonas hydrophila A₂₃G₂₉C₂₁T₁₆ Escherichiacoli A₂₃G₂₉C₂₁T₁₆ Pseudomonas putida A₂₃G₂₉C₂₁T₁₇ Escherichia coliA₂₃G₂₉C₂₂T₁₅ Shigella dysenteriae A₂₃G₂₉C₂₂T₁₅ Vibrio choleraeA₂₃G₃₀C₂₁T₁₆ Aeromonas hydrophila A₂₃G₃₁C₂₁T₁₅ Aeromonas salmonicidaA₂₃G₃₁C₂₁T₁₅ Mycoplasma genitalium A₂₄G₁₉C₁₂T₁₈ Clostridium botulinumA₂₄G₂₅C₁₈T₂₀ Bordetella bronchiseptica A₂₄G₂₆C₁₉T₁₄ Francisellatularensis A₂₄G₂₆C₁₉T₁₉ Bacillus anthracis A₂₄G₂₆C₂₀T₁₈ Campylobacterjejuni A₂₄G₂₆C₂₀T₁₈ Staphylococcus aureus A₂₄G₂₆C₂₀T₁₈ Helicobacterpylori A₂₄G₂₆C₂₀T₁₉ Helicobacter pylori A₂₄G₂₆C₂₁T₁₈ Moraxellacatarrhalis A₂₄G₂₆C₂₃T₁₆ Haemophilus influenzae Rd A₂₄G₂₈C₂₀T₁₇Chlamydia trachomatis A₂₄G₂₈C₂₁T₁₆ Chlamydophila pneumoniae A₂₄G₂₈C₂₁T₁₆C. pneumonia AR39 A₂₄G₂₈C₂₁T₁₆ Pseudomonas putida A₂₄G₂₉C₂₁T₁₆ Proteusvulgaris A₂₄G₃₀C₂₁T₁₅ Yersinia pestis A₂₄G₃₀C₂₁T₁₅ Yersiniapseudotuberculos A₂₄G₃₀C₂₁T₁₅ Clostridium botulinum A₂₅G₂₄C₁₈T₂₁Clostridium tetani A₂₅G₂₅C₁₈T₂₀ Francisella tularensis A₂₅G₂₅C₁₉T₁₉Acinetobacter calcoacetic A₂₅G₂₆C₂₀T₁₉ Bacteriodes fragilis A₂₅G₂₇C₁₆T₂₂Chlamydophila psittaci A₂₅G₂₇C₂₁T₁₆ Borrelia burgdorferi A₂₅G₂₉C₁₇T₁₉Streptobacillus monilifor A₂₆G₂₆C₂₀T₁₆ Rickettsia prowazekiiA₂₆G₂₈C₁₈T₁₈ Rickettsia rickettsii A₂₆G₂₈C₂₀T₁₆ Mycoplasma mycoidesA₂₈G₂₃C₁₆T₂₀

[0116] The same organism having different base compositions aredifferent strains. Groups of organisms which are highlighted or initalics have the same base compositions in the amplified region. Some ofthese organisms can be distinguished using multiple primers. Forexample, Bacillus anthracis can be distinguished from Bacillus cereusand Bacillus thuringiensis using the primer 16S_(—)971-1062 (Table 6).Other primer pairs which produce unique base composition signatures areshown in Table 6 (bold). Clusters containing very similar threat andubiquitous non-threat organisms (e.g. anthracis cluster) aredistinguished at high resolution with focused sets of primer pairs. Theknown biowarfare agents in Table 6 are Bacillus anthracis, Yersiniapestis, Francisella tularensis and Rickettsia prowazekii. TABLE 7Organism 16S_971-1062 16S_1228-1310 16S_1100-1188 Aeromonas hydrophilaA₂₁G₂₉C₂₂T₂₀ A₂₂G₂₇C₂₁T₁₃ A₂₃G₃₁C₂₁T₁₅ Aeromonas salmonicidaA₂₁G₂₉C₂₂T₂₀ A₂₂G₂₇C₂₁T₁₃ A₂₃G₃₁C₂₁T₁₅ Bacillus anthracis A₂₁G₂₇C₂₂T₂₂A₂₄G₂₂C₁₉T₁₈ A₂₃G₂₇C₂₀T₁₈ Bacillus cereus A₂₂G₂₇C₂₁T₂₂ A₂₄G₂₂C₁₉T₁₈A₂₃G₂₇C₂₀T₁₈ Bacillus thuringiensis A₂₂G₂₇C₂₁T₂₂ A₂₄G₂₂C₁₉T₁₈A₂₃G₂₇C₂₀T₁₈ Chlamydia trachomatis A₂₂G₂₆C₂₀T₂₃ A₂₄G₂₃C₁₉T₁₆A₂₄G₂₈C₂₁T₁₆ Chlamydia pneumoniae AR39 A₂₆G₂₃C₂₀T₂₂ A₂₆G₂₂C₁₆T₁₈A₂₄G₂₈C₂₁T₁₆ Leptospira borgpetersenii A₂₂G₂₆C₂₀T₂₁ A₂₂G₂₅C₂₁T₁₅A₂₃G₂₆C₂₄T₁₅ Leptospira interrogans A₂₂G₂₆C₂₀T₂₁ A₂₂G₂₅C₂₁T₁₅A₂₃G₂₆C₂₄T₁₅ Mycoplasma genitalium A₂₈G₂₃C₁₅T₂₂ A₃₀G₁₈C₁₅T₁₉A₂₄G₁₉C₁₂T₁₈ Mycoplasma pneumoniae A₂₈G₂₃C₁₅T₂₂ A₂₇G₁₉C₁₆T₂₀A₂₃G₂₀C₁₄T₁₆ Escherichia coli A₂₂G₂₈C₂₀T₂₂ A₂₄G₂₅C₂₁T₁₃ A₂₃G₂₉C₂₂T₁₅Shigella dysenteriae A₂₂G₂₈C₂₁T₂₁ A₂₄G₂₅C₂₁T₁₃ A₂₃G₂₉C₂₂T₁₅ Proteusvulgaris A₂₃G₂₆C₂₂T₂₁ A₂₆G₂₄C₁₉T₁₄ A₂₄G₃₀C₂₁T₁₅ Yersinia pestisA₂₄G₂₅C₂₁T₂₂ A₂₅G₂₄C₂₀1₁₄ A₂₄G₃₀C₂₁T₁₅ Yersinia pseudotuberculosisA₂₄G₂₅C₂₁T₂₂ A₂₅G₂₄C₂₀T₁₄ A₂₄G₃₀C₂₁T₁₅ Francisella tularensisA₂₀G₂₅C₂₁T₂₃ A₂₃G₂₆C₁₇T₁₇ A₂₄G₂₆C₁₉T₁₉ Rickettsia prowazekiiA₂₁G₂₆C₂₄T₂₅ A₂₄G₂₃C₁₆T₁₉ A₂₆G₂₈C₁₈T₁₈ Rickettsia rickettsiiA₂₁G₂₆C₂₅T₂₄ A₂₄G₂₄C₁₇T₁₇ A₂₆G₂₈C₂₀T₁₆

[0117] The sequence of B. anthracis and B. cereus in region 16S_(—)971is shown below. Shown in bold is the single base difference between thetwo species which can be detected using the methods of the presentinvention. B. anthracis has an ambiguous base at position 20.B.anthracis_16S_971GCGAAGAACCUUACCAGGUNUUGACAUCCUCUGACAACCCUAGAGAUAGGGCU (SEQ ID NO:1)UCUCCUUCGGGAGCAGAGUGACAGGUGGUGCAUGGUU B.cereus_16S_971GCGAAGAACCUUACCAGGUCUUGACAUCCUCUGAAAACCCUAGAGAUAGGGCU (SEQ ID NO:2)UCUCCUUCGGGAGCAGAGUGACAGGUGGUGCAUGGUU

Example 6 ESI-TOF MS of sspE 56-mer Plus Calibrant

[0118] The mass measurement accuracy that can be obtained using aninternal mass standard in the ESI-MS study of PCR products is shown inFIG. 8. The mass standard was a 20-mer phosphorothioate oligonucleotideadded to a solution containing a 56-mer PCR product from the B.anthracis spore coat protein sspE. The mass of the expected PCR productdistinguishes B. anthracis from other species of Bacillus such as B.thuringiensis and B. cereus.

Example 7 B. anthracis ESI-TOF Synthetic 16S_(—)1228 Duplex

[0119] An ESI-TOF MS spectrum was obtained from an aqueous solutioncontaining 5 μM each of synthetic analogs of the expected forward andreverse PCR products from the nucleotide 1228 region of the B. anthracis16S rRNA gene. The results (FIG. 9) show that the molecular weights ofthe forward and reverse strands can be accurately determined and easilydistinguish the two strands. The [M-21H⁺]²¹⁻ and [M-20H⁺]²⁰⁻ chargestates are shown.

Example 8 ESI-FTICR-MS of Synthetic B. anthracis 16S_(—)1337 46 BasePair Duplex

[0120] An ESI-FTICR-MS spectrum was obtained from an aqueous solutioncontaining 5 μM each of synthetic analogs of the expected forward andreverse PCR products from the nucleotide 1337 region of the B. anthracis16S rRNA gene. The results (FIG. 10) show that the molecular weights ofthe strands can be distinguished by this method. The [M-16H⁺]¹⁶⁻ through[M-10H⁺]¹⁰⁻ charge states are shown. The insert highlights theresolution that can be realized on the FTICR-MS instrument, which allowsthe charge state of the ion to be determined from the mass differencebetween peaks differing by a single 13C substitution.

Example 9 ESI-TOF MS of 56-mer Oligonucleotide from saspB Gene of B.anthracis with Internal Mass Standard

[0121] ESI-TOF MS spectra were obtained on a synthetic 56-meroligonucleotide (5 μM) from the saspB gene of B. anthracis containing aninternal mass standard at an ESI of 1.7 μL/min as a function of sampleconsumption. The results (FIG. 11) show that the signal to noise isimproved as more scans are summed, and that the standard and the productare visible after only 100 scans.

Example 10 ESI-TOF MS of an Internal Standard with Tributylammonium(TBA)-trifluoroacetate (TFA) Buffer

[0122] An ESI-TOF-MS spectrum of a 20-mer phosphorothioate mass standardwas obtained following addition of 5 mM TBA-TFA buffer to the solution.This buffer strips charge from the oligonucleotide and shifts the mostabundant charge state from [M-8H⁺]⁸⁻ to [M-3H⁺]³⁻ (FIG. 12).

Example 11 Master Database Comparison

[0123] The molecular masses obtained through Examples 1-10 are comparedto molecular masses of known bioagents stored in a master database toobtain a high probability matching molecular mass.

Example 12 Master Data Base Interrogation Over the Internet

[0124] The same procedure as in Example 11 is followed except that thelocal computer did not store the Master database. The Master database isinterrogated over an internet connection, searching for a molecular massmatch.

Example 13 Master Database Updating

[0125] The same procedure as in example 11 is followed except the localcomputer is connected to the internet and has the ability to store amaster database locally. The local computer system periodically, or atthe user's discretion, interrogates the Master database, synchronizingthe local master database with the global Master database. This providesthe current molecular mass information to both the local database aswell as to the global Master database. This further provides more of aglobalized knowledge base.

Example 14 Global Database Updating

[0126] The same procedure as in example 13 is followed except there arenumerous such local stations throughout the world. The synchronizationof each database adds to the diversity of information and diversity ofthe molecular masses of known bioagents.

[0127] Various modifications of the invention, in addition to thosedescribed herein, will be apparent to those skilled in the art from theforegoing description. Such modifications are also intended to fallwithin the scope of the appended claims. Each reference cited in thepresent application is incorporated herein by reference in its entirety.

1 7 1 90 RNA Bacillus anthracis misc_feature (20)..(20) N = A, U, G or C1 gcgaagaacc uuaccaggun uugacauccu cugacaaccc uagagauagg gcuucuccuu 60cgggagcaga gugacaggug gugcaugguu 90 2 90 RNA Bacillus cereus 2gcgaagaacc uuaccagguc uugacauccu cugaaaaccc uagagauagg gcuucuccuu 60cgggagcaga gugacaggug gugcaugguu 90 3 1542 RNA Artificial Sequencemisc_feature 16S rRNA consensus sequence 3 nnnnnnnaga guuugaucnuggcucagnnn gaacgcuggc ggnnngcnun anacaugcaa 60 gucgancgnn nnnnnnnnnnnnnnnnnnnn nnnnnnnnnn agnggcnnac gggugaguaa 120 nncnunnnna nnunccnnnnnnnnnggnan annnnnnnga aannnnnnnu aauaccnnau 180 nnnnnnnnnn nnnnaaagnnnnnnnnnnnn nnnnnnnnnn nnnnnngann nnnnnnngnn 240 nnaunagnun guuggunngguaanggcnna ccaagncnnn gannnnuagc ngnncugaga 300 ggnngnncng ccacanuggnacugaganac ggnccanacu ccuacgggag gcagcagunn 360 ggaaunuunn ncaauggnngnaanncugan nnagcnannc cgcgugnnng anganggnnu 420 nnngnungua aannncununnnnnnngang annnnnnnnn nnnnnnnnnn nnnnnnnnnu 480 gacnnuannn nnnnannaagnnncggcnaa cuncgugcca gcagccgcgg uaauacgnag 540 gnngcnagcg uunnncgganunanugggcg uaaagngnnn gnaggnggnn nnnnnngunn 600 nnngunaaan nnnnnngcunaacnnnnnnn nnncnnnnnn nacnnnnnnn cungagnnnn 660 nnagnggnnn nnngaauunnnnguguagng gugnaauncg naganaunng nangaanacc 720 nnungcgaag gcnnnnnncuggnnnnnnac ugacncunan nnncgaaagc nugggnagcn 780 aacaggauua gauacccugguaguccangc nnuaaacgnu gnnnnnunnn ngnnngnnnn 840 nnnnnnnnnn nnnnnnnnnannnaacgnnn uaannnnncc gccuggggag uacgnncgca 900 agnnunaaac ucaaangaauugacggggnc cngcacaagc ngnggagnau guggnuuaau 960 ucgangnnac gcgnanaaccuuaccnnnnn uugacaunnn nnnnnnnnnn nnganannnn 1020 nnnnnnnnnn nnnnnnnnnnnnnacaggug nugcauggnu gucgucagcu cgugnnguga 1080 gnuguugggu uaagucccgnaacgagcgca acccnnnnnn nnnguuncna ncnnnnnnnn 1140 ngngnacucn nnnnnnacugccnnngnnaa nnnggaggaa ggnggggang acgucaanuc 1200 nucaugnccc uuangnnnngggcuncacac nuncuacaau ggnnnnnaca nngngnngcn 1260 annnngnnan nnnnagcnaancnnnnaaan nnnnucnnag uncggaungn nnncugcaac 1320 ucgnnnncnu gaagnngganucgcuaguaa ucgnnnauca gnangnnncg gugaauacgu 1380 ucncgggncu uguacacaccgcccgucann ncangnnagn nnnnnnnncc nnaagnnnnn 1440 nnnnnnncnn nnnngnnnnnnnnnncnang gnnnnnnnnn nganugggnn naagucguaa 1500 caagguancc nuannngaannugnggnugg aucaccuccu un 1542 4 2904 RNA Artificial Sequencemisc_feature 23S rRNA consensus sequence 4 nnnnaagnnn nnaagngnnnnngguggaug ccunggcnnn nnnagncgan gaaggangnn 60 nnnnncnncn nnanncnnnggnnagnngnn nnnnnncnnn nnanccnnng nunuccgaau 120 ggggnaaccc nnnnnnnnnnnnnnnnnnan nnnnnnnnnn nnnnnnnnnn nnnnnnngnn 180 nacnnnnnga anugaaacaucunaguannn nnaggaanag aaannaannn ngauuncnnn 240 nguagnggcg agcgaannngnannagncnn nnnnnnnnnn nnnnnnnnnn nnnannngaa 300 nnnnnuggna agnnnnnnnnnannngguna nannccngua nnnnaaannn nnnnnnnnnn 360 nnnnnnnnnn aguannncnnnncncgngnn annnngunng aannngnnnn gaccannnnn 420 naagncuaaa uacunnnnnnngaccnauag ngnannagua cngugangga aaggngaaaa 480 gnacccnnnn nangggagugaaanagnncc ugaaaccnnn nncnuanaan nngunnnagn 540 nnnnnnnnnn nnnuganngcgunccuuuug nannaugnnn cngnganuun nnnunnnnng 600 cnagnuuaan nnnnnnnngnagncgnagng aaancgagun nnaanngngc gnnnagunnn 660 nngnnnnaga cncgaancnnngugancuan nnaugnncag gnugaagnnn nnguaanann 720 nnnuggaggn ccgaacnnnnnnnnguugaa aannnnnngg augannugug nnungnggng 780 aaanncnaan cnaacnnngnnauagcuggu ucucnncgaa annnnuuuag gnnnngcnun 840 nnnnnnnnnn nnnnggngguagagcacugn nnnnnnnnng gnnnnnnnnn nnnnuacnna 900 nnnnnnnnaa acuncgaaunccnnnnnnnn nnnnnnnngn agnnanncnn ngngngnuaa 960 nnuncnnngu nnanagggnaacancccaga ncnncnnnua aggncccnaa nnnnnnnnua 1020 aguggnaaan gangugnnnnnncnnanaca nnnaggangu uggcuuagaa gcagccancn 1080 uunaaagann gcguaanagcucacunnucn agnnnnnnng cgcngannau nuancgggnc 1140 uaannnnnnn nccgaannnnnngnnnnnnn nnnnnnnnnn nnnnngguag nngagcgunn 1200 nnnnnnnnnn ngaagnnnnnnngnnannnn nnnuggannn nnnnnnagug ngnaugnngn 1260 naunaguanc gannnnnnnngugananncn nnnncnccgn annncnaagg nuuccnnnnn 1320 nangnunnuc nnnnnngggunagucgnnnc cuaagnngag ncnganangn nuagnngaug 1380 gnnannnggu nnauauuccnnnacnnnnnn nnnnnnnnnn nnnnngacgn nnnnngnnnn 1440 nnnnnnnnnn nnnnggnnnnnnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1500 nnnnnnnnnn nnnnnnnnnnnnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1560 nnnncnngaa aannnnnnnnnnnnnnnnnn nnnnnnnnnc guaccnnaaa ccgacacagg 1620 ungnnnngnn gagnanncnnaggngnnngn nnnaannnnn nnnaaggaac unngcaaanu 1680 nnnnccguan cuucggnanaaggnnnncnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1740 nnnnnnnnng nnnnannnannngnnnnnnn cnacuguuua nnaaaaacac agnncnnugc 1800 naanncgnaa gnnganguauanggnnugac nccugcccng ugcnngaagg uuaanngnnn 1860 nnnnnngnnn nngnnnnnnnnnnnannnaa gcccnnguna acggcggnng uaacuauaac 1920 nnuccuaagg uagcgaaauuccuugucggg uaaguuccga ccngcacgaa nggngnaang 1980 annnnnnnnc ugucucnnnnnnnnncncng ngaanuunna nunnnnguna agaugcnnnn 2040 uncncgcnnn nngacggaaagaccccnngn ancuuuacun nannnunnna nugnnnnnnn 2100 nnnnnnnnug unnagnauaggunggagncn nngannnnnn nncgnnagnn nnnnnggagn 2160 cnnnnnugnn auacnacncunnnnnnnnnn nnnnucuaac nnnnnnnnnn nancnnnnnn 2220 nnngacanug nnngnngggnaguuunacug gggcggunnc cuccnaaann guaacggagg 2280 ngnncnaagg unnncunannnnggnnggnn aucnnnnnnn nagunnaann gnanaagnnn 2340 gcnunacugn nagnnnnacnnnncgagcag nnncgaaagn nggnnnuagu gauccggngg 2400 unnnnnnugg aagngccnucgcucaacgga uaaaagnuac ncnggggaua acaggcunau 2460 nnnncccaag aguncanaucgacggnnnng uuuggcaccu cgaugucggc ucnucncauc 2520 cuggggcugn agnnggucccaagggunngg cuguucgccn nuuaaagngg nacgngagcu 2580 ggguunanaa cgucgugagacaguungguc ccuaucngnn gngngngnnn gannnuugan 2640 nngnnnugnn cnuaguacgagaggaccggn nngnacnnan cncuggugnn ncnguugunn 2700 ngccannngc anngcngnnuagcuannunn ggnnnngaua anngcugaan gcaucuaagn 2760 nngaancnnn cnnnnagannagnnnucncn nnnnnnnnnn nnnnnnnnna gnnncnnnnn 2820 agannannnn gungauaggnnngnnnugna agnnnngnna nnnnunnagn nnacnnnuac 2880 uaaunnnncn nnnnncuunnnnnn 2904 5 13 DNA Artificial Sequence misc_feature Primer 5 cgtggtgaccctt 13 6 14 DNA Artificial Sequence misc_feature Primer 6 cgtcgtcaccgcta 14 7 13 DNA Artificial Sequence misc_feature Primer 7 cgtggtacccctt 13

What is claimed is:
 1. A method of identifying an unknown bioagent in anenvironmental sample using a database of molecular masses of knownbioagents comprising: contacting nucleic acid from said bioagent in saidenvironmental sample with at least one pair of oligonucleotide primersthat hybridize to sequences of said nucleic acid, wherein said sequencesflank a variable nucleic acid sequence of said bioagent in saidenvironmental sample; producing an amplification product of saidvariable nucleic acid sequence; determining a first molecular mass ofsaid amplification product; and comparing said first molecular mass tothe molecular masses of known bioagents, thereby identifying the unknownbioagent in said environmental sample.
 2. The method of claim 1 whereinsaid sequences to which said at least one pair of oligonucleotideprimers hybridize are highly conserved.
 3. The method of claim 1 whereinsaid sequences to which said at least one pair of oligonucleotideprimers hybridize are highly conserved across at least two species. 4.The method of claim 1 further comprising the step of isolating a nucleicacid from said environmental sample prior to contacting said nucleicacid with said at least one pair of oligonucleotide primers, wherein thecomparing step further comprises comparing a base-pair count resultingfrom a translation of the corresponding molecular mass, and wherein amaster database of molecular masses of known bioagents further includesa translation of said molecular masses of known bioagents tocorresponding base-pair counts of each known bioagent resulting from aspecific primer pair set and comparing the base-pair count of saidunknown bioagent against the obtained base-pair count of known bioagentsfor the selected primer pair set for determining the identity of saidunknown bioagent in said environmental sample.
 5. The method of claim 4further comprising the step of reconciling the database of molecularmasses of known bioagents with the master database of molecular massesof known bioagents.
 6. The method of claim 1 wherein said bioagent is abacterium, parasite, fungi, virus, cell or spore.
 7. The method of claim1 wherein said environmental sample is a water sample, air sample, orland sample.
 8. The method of claim 7 wherein said water sample isobtained from a lake, river, ocean, stream, water treatment system,rainwater, groundwater, water table, reservoir, well, or bottled water.9. The method of claim 7 wherein said air sample is obtained from aventilation system, airplane cabin, school, hospital, or mass transitlocation.
 10. The method of claim 9 wherein said mass transit locationis a subway, train station, or airport.
 11. The method of claim 1wherein said amplification product is ionized by electorosprayionization, matrix assisted laser desorption or fast atom bombardmentprior to molecular mass determination.
 12. The method of claim 1 whereinsaid molecular mass is determined by mass spectrometry.
 13. The methodof claim 5 wherein said master database of molecular masses of knownbioagents and the database of molecular masses of known bioagents arereconciled over a network.
 14. The method of claim 4 wherein theidentity is determined by statistically correlating the molecular massof the unknown bioagent with at least one molecular mass of said masterdatabase.
 15. A database having cell-data positional significancecomprising at least a first table of a plurality of data-containingcells, said first table organized into at least a first row and a secondrow, each row having columns and data-containing cells; and wherein saiddata-containing cells have an alignment with at least one other row fordifferentiating aligned from non-aligned data-containing cells, andwherein said differentiation in alignment of said data-containing cellsdesignates a structural feature of a polymer present in an environmentalsample.
 16. The database according to claim 15 wherein said alignment isa vertical alignment according to base pair homology along a linearsegment within each polymer.
 17. The database according to claim 15wherein said vertical alignment further aligns cell-data according tointer-species conserved regions.
 18. The database according to claim 15wherein the structural feature is a bulge or a loop.
 19. The databaseaccording to claim 15 wherein the polymer is an RNA.
 20. The method ofclaim 15 wherein said environmental sample is a water sample, airsample, or land sample.
 21. The method of claim 20 wherein said watersample is obtained from a lake, river, ocean, stream, water treatmentsystem, rainwater, groundwater, water table, reservoir, well, or bottledwater.
 22. The method of claim 20 wherein said air sample is obtainedfrom a ventilation system, airplane cabin, school, hospital, or masstransit location.
 23. The method of claim 22 wherein said mass transitlocation is a subway, train station, or airport.
 24. A service providinginformation related to a bioagent in an environmental sample comprising:providing a dimensional master database for storing a molecular mass, anidentity and a detail corresponding to a plurality of known bioagentsand, said master database storing the molecular mass, the identity andthe detail for a plurality of known bioagents; interrogating the masterdatabase with an identification request of an unknown bioagent in saidenvironmental sample to generate a response; and delivering saidresponse from the master database to a requester.
 25. The serviceaccording to claim 24 wherein the molecular mass is of a selectedportion of the known bioagent, the identity comprises at least ageographic origin and a name for the known bioagent, and the detailcomprises at least a treatment.
 26. The service according to claim 24wherein the request comprises a symptomatology and the identificationcomprises a recommended pair of primers for hybridizing to sequences ofnucleic acid flanking a variable nucleic acid sequence of the unknownbioagent, and said pair of primers are hybridized to the sequences ofnucleic acid flanking a variable nucleic acid sequence of the unknownbioagent.
 27. The service according to claim 26 wherein the nucleic acidsequence of the unknown bioagent between said pair of primers definesthe selected portion of both the known bioagents and the unknownbioagent.
 28. The service according to claim 27 wherein the response isdelivered through a network.
 29. The service according to claim 27wherein the request comprises a molecular mass of the unknown bioagentfor the selected portion and where the response generated theretocomprises a set of molecular masses for analogous selected portions ofknow bioagents, and said set comprising at least one molecular mass fromthe master database.
 30. The service according to claim 28 wherein thenetwork is a local area network.
 31. The service according to claim 28wherein the network is a wide area network.
 32. The service according toclaim 29 wherein the network is the internet.
 33. A method ofdetermining a geographical origin of a selected bioagent in anenvironmental sample using a database of molecular masses of knownbioagents comprising: contacting nucleic acid from said selectedbioagent in said environmental sample with at least one pair ofoligonucleotide primers which hybridize to sequences of said nucleicacid, wherein said sequences flank a variable nucleic acid sequence ofthe bioagent in said environmental sample; producing an amplificationproduct of said variable nucleic acid sequence; determining a firstmolecular mass of said amplification product; and comparing said firstmolecular mass to the molecular masses of known bioagents fordetermining a geographic origin of said selected bioagent, saidcomparison determining an identity and a geographic origin of saidselected bioagent in said environmental sample.
 34. The method of claim33 wherein said sequences to which said at least one pair ofoligonucleotide primers hybridize are highly conserved.
 35. The methodof claim 33 wherein said sequences to which said at least one pair ofoligonucleotide primers hybridize are highly conserved across species.36. The method of claim 33 further comprising the step of isolating anucleic acid from said selected bioagent prior to contacting saidnucleic acid with said at least one pair of oligonucleotide primers,wherein the comparing step further comprises interrogating a masterdatabase of molecular masses of known bioagents for obtaining molecularmasses of known bioagents and comparing the molecular mass of saidselected bioagent against the obtained molecular masses of knownbioagents thereby determining an origin of said selected bioagent. 37.The method of claim 36 further comprising the step of reconciling thedatabase of molecular masses of known bioagents with the master databaseof molecular masses of known bioagents.
 38. The method of claim 33wherein said bioagent is a bacterium, parasite, fungi, virus, ell orspore.
 39. The method of claim 33 wherein said environmental sample is awater sample, air sample, or land sample.
 40. The method of claim 39wherein said water sample is obtained from a lake, river, ocean, stream,water treatment system, rainwater, groundwater, water table, reservoir,well, or bottled water.
 41. The method of claim 39 wherein said airsample is obtained from a ventilation system, airplane cabin, school,hospital, or mass transit location.
 42. The method of claim 41 whereinsaid mass transit location is a subway, train station, or airport. 43.The method of claim 33 wherein said amplification product is ionized byelectorospray ionization, matrix assisted laser desorption or fast atombombardment prior to molecular mass determination.
 44. The method ofclaim 33 wherein said molecular mass is determined by mass spectrometry.45. The method of claim 36 wherein said master database of molecularmasses of known bioagents and the database of molecular masses of knownbioagents are reconciled over a network.
 46. The method of claim 36wherein the origin comprises a statistical group of matching molecularmasses and the geographic origin corresponding thereto.